|
|
Absolute deviation, 绝对离差
( C u5 v' W8 i, t+ j* p8 {Absolute number, 绝对数- M/ t% c8 Q7 R2 S* j2 c0 ~
Absolute residuals, 绝对残差. r; q7 m- n4 h3 d" o9 R# n) {/ h5 k
Acceleration array, 加速度立体阵
% i6 }9 y; q2 O9 j2 l3 V6 D. VAcceleration in an arbitrary direction, 任意方向上的加速度: x8 Q$ k: h, v6 l
Acceleration normal, 法向加速度
9 s3 p$ c- G+ GAcceleration space dimension, 加速度空间的维数, R! i7 A) G T1 Z
Acceleration tangential, 切向加速度5 F5 S3 _# z8 J; c0 ^
Acceleration vector, 加速度向量
5 h& W7 ?7 p6 P4 Z. c7 T( MAcceptable hypothesis, 可接受假设
1 X0 W5 i0 {5 T( YAccumulation, 累积6 h! B3 d+ N, p0 g
Accuracy, 准确度% K5 ]4 q+ E& o" B9 B. S5 j) P L7 z
Actual frequency, 实际频数 r. F {( s% w n2 r+ @
Adaptive estimator, 自适应估计量. v* V4 `, d1 A% w
Addition, 相加! ?3 Q9 s# v6 _/ Y( B1 ^
Addition theorem, 加法定理/ s1 V5 D8 E! V8 A2 B
Additivity, 可加性
/ w' Z3 c' N( S* r* @! }/ BAdjusted rate, 调整率
( H$ a' F. g2 O" T1 AAdjusted value, 校正值0 G- ]6 W5 v! ~# C9 Y
Admissible error, 容许误差
7 F+ ^ j) [% M, L+ e7 `3 eAggregation, 聚集性) u7 @( |$ n( s7 A1 d$ I" i3 }
Alternative hypothesis, 备择假设
: q) A+ Y% V. Q( lAmong groups, 组间% F" g; Q) y+ ~" e
Amounts, 总量
6 Y1 M( @% x% K& g) DAnalysis of correlation, 相关分析0 x. A0 ~# ?' w
Analysis of covariance, 协方差分析. k) S4 p, B5 Z
Analysis of regression, 回归分析- F+ A. v8 E$ V! M1 [
Analysis of time series, 时间序列分析7 v$ D/ D; v% f0 x) }7 |
Analysis of variance, 方差分析
: r& ~ V2 c) XAngular transformation, 角转换
- U- d0 \$ a2 V/ OANOVA （analysis of variance）, 方差分析
K0 _. }2 E6 k4 ^# d8 k7 e5 n# ]/ |ANOVA Models, 方差分析模型
8 D* ]# t; B @9 IArcing, 弧/弧旋) y1 F) E* a# q+ H _
Arcsine transformation, 反正弦变换" b4 D: S5 z: k) G0 g* O; F
Area under the curve, 曲线面积
/ F3 _. d' U# }8 wAREG , 评估从一个时间点到下一个时间点回归相关时的误差
/ f4 o" {; k! j* ]) GARIMA, 季节和非季节性单变量模型的极大似然估计
' M( ~5 H4 J: A. G2 ?Arithmetic grid paper, 算术格纸1 A# O6 W4 k7 K
Arithmetic mean, 算术平均数
7 }+ L6 d$ x9 }) IArrhenius relation, 艾恩尼斯关系
4 l5 n! d' Q% G! OAssessing fit, 拟合的评估- X. Y. r. G2 j& y4 i" S
Associative laws, 结合律, l4 O' W7 J% C% f9 n) W$ h
Asymmetric distribution, 非对称分布' x! M* m& U9 Y) u$ o5 n
Asymptotic bias, 渐近偏倚
" v5 L u0 X1 S% I. M/ T; CAsymptotic efficiency, 渐近效率
* N' F7 n' V4 P) j- B2 xAsymptotic variance, 渐近方差
+ k- m& V1 s( ^6 O/ {Attributable risk, 归因危险度
3 j6 l5 o" o/ a6 i9 X1 P% C& E1 QAttribute data, 属性资料) U4 S7 V M/ u7 n
Attribution, 属性- \* A, Y3 A1 G
Autocorrelation, 自相关0 a+ l) \4 {; ]! d
Autocorrelation of residuals, 残差的自相关
0 |- u' p1 |0 {8 t( N5 dAverage, 平均数% u" _ w1 E8 _' i. o
Average confidence interval length, 平均置信区间长度
3 ]- L& g4 B( D' G4 oAverage growth rate, 平均增长率
Z, w) F1 F9 GBar chart, 条形图
* O+ S0 o0 L5 ]: e3 e& ]: cBar graph, 条形图
4 O- M# R" R8 e" H2 S7 ?* [/ z/ f$ j$ aBase period, 基期" s; i0 `2 ^* ~( G, D3 w
Bayes' theorem , Bayes定理
4 {0 ?1 z2 ]2 b E8 Z* cBell-shaped curve, 钟形曲线 a, }5 F6 l) S
Bernoulli distribution, 伯努力分布
' B* ]1 I& Y5 K3 hBest-trim estimator, 最好切尾估计量& u. N, i6 w! J( |. e" b- C0 I- `
Bias, 偏性, W0 d$ [+ n" B" `
Binary logistic regression, 二元逻辑斯蒂回归/ |; E2 k0 z. n9 y( j$ ?
Binomial distribution, 二项分布
. i8 l) s% i; N9 `) @Bisquare, 双平方
% b# d$ ~9 m- E6 L0 CBivariate Correlate, 二变量相关
! G3 O, J' e- p/ x2 X6 _: nBivariate normal distribution, 双变量正态分布, o8 Z) y; i' H1 C9 a/ L
Bivariate normal population, 双变量正态总体
$ v& b: x, b, x5 q- I% X' FBiweight interval, 双权区间+ y4 Q3 O6 [2 ]& |
Biweight M-estimator, 双权M估计量
) p5 n5 a" E" p4 P DBlock, 区组/配伍组 _1 l# ~' g4 k5 U+ P) X/ {. D
BMDP(Biomedical computer programs), BMDP统计软件包& a+ x' q& e% }3 O
Boxplots, 箱线图/箱尾图8 {" Q: L# }1 h8 u1 Y1 A8 ~
Breakdown bound, 崩溃界/崩溃点 p# Z. f% Z3 |; ?
Canonical correlation, 典型相关
* L5 i! q4 H& d1 M- X( gCaption, 纵标目3 u$ {# n, y* w- X4 J0 m
Case-control study, 病例对照研究
$ x* R% B" T( l) fCategorical variable, 分类变量* E& F' }0 a% p6 Q
Catenary, 悬链线
/ q+ d" b% t" N j: U8 B, r( B; uCauchy distribution, 柯西分布
# l3 h& N$ q0 Z jCause-and-effect relationship, 因果关系% x: l) e0 _, q+ l
Cell, 单元5 D) C! T2 c8 }; \( f' A
Censoring, 终检
$ Q, l2 m* G5 m& Q% r* UCenter of symmetry, 对称中心0 h/ [6 h: X3 @) n; Z: X' V8 ?; t
Centering and scaling, 中心化和定标
7 Z( B9 ~4 l- N( yCentral tendency, 集中趋势5 r# L: U$ ]1 z8 A; U! z
Central value, 中心值% R4 k- t) @! Z* {6 |' T' J
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测2 u4 w( F& @6 v1 d, G: Q
Chance, 机遇
8 s2 o9 F' }2 V$ P/ T6 ?' c( }Chance error, 随机误差
3 x: C5 K3 t# O! y5 g: t/ K" {- U, ~( mChance variable, 随机变量
, e( w: @' I( K. z& @, A( H, FCharacteristic equation, 特征方程& O/ [3 Z0 J% f0 ^0 T; m
Characteristic root, 特征根5 g% a7 A% q, t+ U- N% o0 _
Characteristic vector, 特征向量
0 I: U% X$ t! m- b* f# e& PChebshev criterion of fit, 拟合的切比雪夫准则
1 o! s* h; |7 [! Q% @7 P# a! rChernoff faces, 切尔诺夫脸谱图8 d- Y5 z3 K" V/ J' C. }
Chi-square test, 卡方检验/χ2检验& K- M& D& `* o- }2 I8 U7 ~+ z' i
Choleskey decomposition, 乔洛斯基分解) D$ h+ ]7 j5 l! y F* a
Circle chart, 圆图
! _; |- O5 p; e! \- \& }& |Class interval, 组距" S5 R* U9 K& ^+ x( m7 l
Class mid-value, 组中值+ g& j0 d3 i6 @, y' ]$ h2 q
Class upper limit, 组上限4 u6 _- K' U7 K7 W& Q2 t
Classified variable, 分类变量
/ H6 ?& t" F1 Z) n; Q0 |, UCluster analysis, 聚类分析' y0 r# ~" q2 w4 Q9 H8 T# t
Cluster sampling, 整群抽样- o8 H) n0 p5 j+ R: y0 e
Code, 代码! S1 ^) M: t. b3 q! ~5 h- f/ a
Coded data, 编码数据
* O1 Q- y8 }/ r" M+ xCoding, 编码 D& @' L: L) Z4 w( w' s
Coefficient of contingency, 列联系数
3 [9 d! g2 V0 n& l5 F% O3 s" _& f" kCoefficient of determination, 决定系数
: T3 \; O" m' V! X, U- K. A2 @+ N0 _Coefficient of multiple correlation, 多重相关系数# G* b+ m, u7 w, Y; g; w
Coefficient of partial correlation, 偏相关系数
2 O- J2 {) `4 j' V% l" O ?Coefficient of production-moment correlation, 积差相关系数
) L1 k$ ~+ g) n( HCoefficient of rank correlation, 等级相关系数
6 m& z9 v# A, K1 U$ RCoefficient of regression, 回归系数. f, a- n( Y4 Z/ B" J" g7 D
Coefficient of skewness, 偏度系数- O1 I1 w: v5 |" s1 A* v; B
Coefficient of variation, 变异系数" K# ]- m" v9 D: ]) y, r' L
Cohort study, 队列研究
2 E) Y' j$ ?2 a& P3 d! G2 J$ VColumn, 列4 g. I9 h0 \( d8 a% Y9 O4 E- |1 }
Column effect, 列效应
" l* O" ?" K4 g" v5 X) X! L( ^1 [Column factor, 列因素! J) q4 t0 W! N
Combination pool, 合并; D( H% M- N( M+ A
Combinative table, 组合表( q! H' L" ~7 h) x
Common factor, 共性因子
4 }# ~% [# F$ ~3 K4 z4 M6 i4 X" ZCommon regression coefficient, 公共回归系数
, @3 k$ A4 [" a* a) F' OCommon value, 共同值# o3 G* {2 c/ K9 I3 Q
Common variance, 公共方差
# N1 e5 }5 [( y8 lCommon variation, 公共变异; a& ]* l! K' P, H0 P+ a) W6 F
Communality variance, 共性方差0 e! F U7 F/ D8 F7 D- N& F) d
Comparability, 可比性5 w" i/ }/ S! g9 y \# t' U; c# a
Comparison of bathes, 批比较
9 O' r6 }* h- q+ M2 H1 qComparison value, 比较值6 Y/ P: v9 |/ j6 q. T/ X# m
Compartment model, 分部模型
/ G. S8 N8 ? LCompassion, 伸缩
; F2 N9 r0 ~' b3 ^ KComplement of an event, 补事件
( l, h. k* n# ?5 r* ~9 NComplete association, 完全正相关
. ?/ O6 C# [" A/ z' T* gComplete dissociation, 完全不相关4 U% M5 P; D( ~
Complete statistics, 完备统计量
& g" d2 j1 ?6 p& Q" tCompletely randomized design, 完全随机化设计
+ z( R3 V @' ~Composite event, 联合事件. l N% l, q) f7 ~. k# Z
Composite events, 复合事件
6 d1 \% {$ q9 o3 L5 W4 oConcavity, 凹性
4 a, J& r0 x0 O/ M/ G9 _7 g2 zConditional expectation, 条件期望
4 i: X8 d2 g' O1 b$ V: ?* t% l: [Conditional likelihood, 条件似然
# d h& |+ ?6 c9 B7 k8 h: I/ E ]' |Conditional probability, 条件概率* r0 v, C% T: [1 i4 ~5 B" g1 D$ c
Conditionally linear, 依条件线性( Q/ N9 ]6 |1 ]( G8 [/ C0 O A' u
Confidence interval, 置信区间( J) B% q% b) B% ^7 g
Confidence limit, 置信限; x4 `6 ?( A4 K. ^ P2 f
Confidence lower limit, 置信下限
5 I. d' W' C9 ^) z0 {Confidence upper limit, 置信上限7 V2 F( D/ t2 \6 w4 ^( t( @
Confirmatory Factor Analysis , 验证性因子分析0 @# z9 r( n% Y0 c
Confirmatory research, 证实性实验研究
* n# a2 t% p6 W& }# o3 v ~Confounding factor, 混杂因素
; t( `5 D: |7 F, D9 sConjoint, 联合分析
' ]. h5 ]. I0 E. s1 cConsistency, 相合性 l! c. p/ j# g3 S
Consistency check, 一致性检验
/ e9 P- N3 r0 }6 |6 I# d3 O7 ?2 Y2 \Consistent asymptotically normal estimate, 相合渐近正态估计
+ l4 O" F7 m' |" T/ f; l5 N U- VConsistent estimate, 相合估计' N' Y5 u! P5 C
Constrained nonlinear regression, 受约束非线性回归
; ~ X/ M+ a& W& m6 t; W) K2 DConstraint, 约束! }! q2 j0 _3 J f
Contaminated distribution, 污染分布, w) q, m9 z( w7 c* V1 [, S; {
Contaminated Gausssian, 污染高斯分布
. R( b# q4 l3 P5 K( PContaminated normal distribution, 污染正态分布
/ i' H X/ J5 xContamination, 污染
L0 }) J d* rContamination model, 污染模型
/ J6 ^3 H) L9 w) U! z; `; g& ?' _/ JContingency table, 列联表% f$ u7 Y, i' _$ d* z
Contour, 边界线 g2 w, U1 O! @' O
Contribution rate, 贡献率
, V+ {2 N1 m! O9 FControl, 对照: ~' } _: X" e% @) H
Controlled experiments, 对照实验
; @0 f+ d* s8 A: ^& K# R- CConventional depth, 常规深度
3 D* F4 q: L( L: r# EConvolution, 卷积 B( C* G R' b9 V6 i9 N3 _% `- I
Corrected factor, 校正因子& m+ e/ @8 D2 d- G+ E
Corrected mean, 校正均值: h9 I, O2 N6 Z g
Correction coefficient, 校正系数 e0 {: n1 d: ~' X: b% ~
Correctness, 正确性
/ p) a' B) x# }& R0 l+ q0 J! x9 jCorrelation coefficient, 相关系数
7 R; ]" v" Y( P2 e1 T" ^: c. xCorrelation index, 相关指数
3 d" X. {2 y2 Q: j5 PCorrespondence, 对应4 Y) l+ o4 y+ f5 n2 C2 V# n
Counting, 计数# m. {1 U, x, D' ]% }
Counts, 计数/频数0 ?; j) `1 d! w' P1 v
Covariance, 协方差
" _& m4 j( V5 i8 F$ UCovariant, 共变 - R; j6 l& K/ B, v" x
Cox Regression, Cox回归2 ^; W, k8 ~3 n% ?5 b
Criteria for fitting, 拟合准则! R1 V2 p6 n- r/ z+ M- e: t1 h
Criteria of least squares, 最小二乘准则
% D4 x9 b7 I1 Y: e7 sCritical ratio, 临界比
( U# [8 ]0 a$ ?4 p. Z8 [Critical region, 拒绝域2 k* W+ [) H8 N5 c: k- A
Critical value, 临界值
: G* m9 N# A5 \3 ]( Y# qCross-over design, 交叉设计. _# l) N0 Z# k3 l
Cross-section analysis, 横断面分析1 X* [; |2 D% U+ ~
Cross-section survey, 横断面调查6 U5 p6 K! A2 T1 f/ X u
Crosstabs , 交叉表
5 C8 s0 [9 p3 g3 x; GCross-tabulation table, 复合表3 ~1 |% J( j/ [$ N% Y
Cube root, 立方根( ^" y$ n* b$ Q' l
Cumulative distribution function, 分布函数
1 N9 j Q3 {# d+ {Cumulative probability, 累计概率
% J: c0 d. i7 g! I0 ~6 FCurvature, 曲率/弯曲& y0 {% Y' M% \
Curvature, 曲率. N7 J" b6 v. o( q5 ?' l# B+ P
Curve fit , 曲线拟和
( L6 \6 O- ^/ r8 fCurve fitting, 曲线拟合
7 e+ a8 F* l% j* U( MCurvilinear regression, 曲线回归
5 @1 o/ w) F- a$ ^6 `; O# b) BCurvilinear relation, 曲线关系
5 c+ [4 y* j8 j2 T3 Y) Y" Q6 BCut-and-try method, 尝试法
o5 \3 M$ `" r, w- x( F' ?Cycle, 周期
' V& t( _# `' A( t* \$ ICyclist, 周期性
1 m! [% [: ~8 U" w6 W7 F7 tD test, D检验
( l8 t) j1 f4 e& mData acquisition, 资料收集
4 H2 P' a7 O8 ^Data bank, 数据库6 D# D! I. F- X
Data capacity, 数据容量+ h) ^9 b: j) o- S( H" e9 C4 Z
Data deficiencies, 数据缺乏% [* `- c: b% e) V$ Y4 J# T. S. n1 \+ |
Data handling, 数据处理1 Y6 ~/ b! B, }! A( G0 E8 u+ h
Data manipulation, 数据处理
; `, D: D0 R) x; h/ v: FData processing, 数据处理
% ?2 X$ T" A, o8 `, pData reduction, 数据缩减
$ w, X9 w9 Y. V2 L: K8 G* {Data set, 数据集
( \% l K- P1 z1 B9 Z5 E8 eData sources, 数据来源9 x. N% r" m, W5 \4 V% [
Data transformation, 数据变换
- \' Y& x. t5 k% G$ A. v' YData validity, 数据有效性
. f& e) B$ ]. I0 qData-in, 数据输入4 F: v; u: X, v' @5 N: ^4 x# [0 U
Data-out, 数据输出
2 @) x: T3 k: VDead time, 停滞期
) a6 j) w: P) e0 Z0 aDegree of freedom, 自由度
/ S% f/ D9 B# L- Q6 Q$ [7 ZDegree of precision, 精密度
" K2 J: i! a* A% lDegree of reliability, 可靠性程度
! j) R! h D' t: a. s, e+ ?Degression, 递减
) d6 v, U4 _+ ? xDensity function, 密度函数& }3 ~3 W2 ^- L/ X6 ^, i( I
Density of data points, 数据点的密度
: m8 [" f: ^, Z5 R( w1 pDependent variable, 应变量/依变量/因变量
* \6 R: r V9 b) \9 ? v QDependent variable, 因变量4 D( x& u4 E+ [! [* z* K6 I
Depth, 深度+ Q! P- o5 G, r2 ~
Derivative matrix, 导数矩阵
: t* ~1 P: F5 t8 }6 u6 W. J' oDerivative-free methods, 无导数方法
1 U( q; x7 \9 V2 t, E2 p: _0 [Design, 设计+ b' q; T- M7 \0 U$ [
Determinacy, 确定性
7 H4 F! g. b( i/ ADeterminant, 行列式
' i) Z1 w" Z% iDeterminant, 决定因素: P0 \/ Q, `& q6 ~$ O& `% t" M( L1 Q
Deviation, 离差
+ \- e5 b/ ^/ iDeviation from average, 离均差
* P$ H, Q4 ^; q' I9 p DDiagnostic plot, 诊断图; n2 Z4 T. p4 L- @0 f8 P) C% d
Dichotomous variable, 二分变量
3 ~6 u$ w9 d: ~ p; J" Q& f9 PDifferential equation, 微分方程5 {& v1 t. J Q; v* s8 s
Direct standardization, 直接标准化法' s5 s' u" x9 u, v9 Y! B/ \- Q: n
Discrete variable, 离散型变量) g Q7 D5 ]8 r |. ^
DISCRIMINANT, 判断 v ]! ], R& l
Discriminant analysis, 判别分析
. t/ T; m) T5 E ` NDiscriminant coefficient, 判别系数
% H0 U6 F: R: S" LDiscriminant function, 判别值
7 H; F& p& c/ w6 ^: d+ cDispersion, 散布/分散度
3 ]1 Y8 ~4 G# S% H }Disproportional, 不成比例的
3 _# p4 ^1 D) k8 \3 j& h! l, E3 a( ODisproportionate sub-class numbers, 不成比例次级组含量6 V3 k& Y# L# ]( M
Distribution free, 分布无关性/免分布/ l) N( j: U E
Distribution shape, 分布形状$ ~) f3 m; N. S8 C: j
Distribution-free method, 任意分布法7 `( ~7 p# F$ m% H2 ?6 B
Distributive laws, 分配律) |6 V2 B9 E. T+ {# D2 x9 K
Disturbance, 随机扰动项
: i5 V: T" q6 p* S- BDose response curve, 剂量反应曲线 v. [0 H: N8 \5 S
Double blind method, 双盲法( p8 l( Q+ L7 s) S
Double blind trial, 双盲试验
, Y! u$ Q/ i( h/ i1 c/ R6 h; i1 RDouble exponential distribution, 双指数分布# r5 e( n1 K, i
Double logarithmic, 双对数7 J$ }7 a1 C. k- w
Downward rank, 降秩
' Y. O. d; k( Z$ D$ Q6 u4 kDual-space plot, 对偶空间图
2 Q+ X3 ^& I' w0 t: i- S- kDUD, 无导数方法
: R; v5 l: m w. w+ sDuncan's new multiple range method, 新复极差法/Duncan新法$ i+ y) D) K' ^
Effect, 实验效应2 S4 i$ J+ z9 Y T6 R
Eigenvalue, 特征值
0 Q/ \9 C& M. @9 M7 I9 zEigenvector, 特征向量
, C# R3 X( X. `: h1 WEllipse, 椭圆. c+ e8 S# j. N3 G5 Y: k
Empirical distribution, 经验分布8 Z9 z% B8 w: o3 G8 e% U2 m
Empirical probability, 经验概率单位8 ^+ N$ s( N' _" `
Enumeration data, 计数资料# I5 n2 f1 f0 N8 a/ G5 H
Equal sun-class number, 相等次级组含量. z2 Z& F, d ?$ t
Equally likely, 等可能
" Y. s( U" A- m) g5 T6 M( `Equivariance, 同变性
) C+ u7 D. `" Q7 i9 \: OError, 误差/错误 q7 w- |" n$ t1 @# D
Error of estimate, 估计误差
# v i7 [: X7 Q) x( sError type I, 第一类错误
! `$ i+ j8 d. P+ x# QError type II, 第二类错误
5 M$ m/ w1 a' D( w3 gEstimand, 被估量$ W! H( {; U# b# a
Estimated error mean squares, 估计误差均方( _$ D, W) r. }* s) a/ L
Estimated error sum of squares, 估计误差平方和& s# \, ^! I5 Y& j
Euclidean distance, 欧式距离/ [. I9 ]3 b; }' D6 ~+ k8 A
Event, 事件( k6 a" V4 f" T+ g- |+ w
Event, 事件
+ I9 G. Q3 l+ m/ C W% P' mExceptional data point, 异常数据点
, G$ w" r! U: d9 X# r) V. A0 mExpectation plane, 期望平面- E5 p6 t( u! }2 P' `1 K
Expectation surface, 期望曲面8 }! z' k$ C' E( B( r# _. u$ L: t/ t
Expected values, 期望值/ v# k8 U [ _ j9 `3 ]4 j: v
Experiment, 实验
8 l2 M6 _3 m# _2 ?$ pExperimental sampling, 试验抽样( U" P( x$ M" t7 s& r
Experimental unit, 试验单位
: c; _ Y# \& M$ z, v6 nExplanatory variable, 说明变量( x/ o v0 F! ^. A
Exploratory data analysis, 探索性数据分析( d7 I$ I6 N i8 y" G. D5 Y& G
Explore Summarize, 探索-摘要
- ]6 A4 F: m% e' D1 UExponential curve, 指数曲线
% W5 `$ b, z# X) D) @% QExponential growth, 指数式增长
$ e# w% A2 t+ {4 \% I/ HEXSMOOTH, 指数平滑方法 ! A k4 |" H6 K1 g3 o( n
Extended fit, 扩充拟合: u' b. h& G3 H( I; o1 p8 N5 \9 c
Extra parameter, 附加参数
5 T0 U3 M3 [4 WExtrapolation, 外推法
# y/ o; {6 g$ D6 A2 NExtreme observation, 末端观测值
% j+ g! H8 x7 y, l9 t6 T% P( NExtremes, 极端值/极值7 Z+ N l9 S" k! A) A# }# a
F distribution, F分布
: N$ i) ]2 z n! B3 _7 sF test, F检验
" y, }* c! k% i) WFactor, 因素/因子* `+ r! j) E4 R0 n: Z
Factor analysis, 因子分析2 M5 |& L* C2 C* t5 I2 ]( q
Factor Analysis, 因子分析 r$ x8 d+ s1 z, j
Factor score, 因子得分 9 I, }9 Y; ?' B2 W
Factorial, 阶乘4 @% k4 H; V* ]8 H! K* G" k! _, t. B
Factorial design, 析因试验设计
5 T: U) g! y, J. o' L E3 NFalse negative, 假阴性
# N' ~4 b. [1 K, KFalse negative error, 假阴性错误, F* v+ t! n" j% M) F. \0 J/ O" {8 X1 s2 d
Family of distributions, 分布族, f8 T- L: ]) S2 N2 l
Family of estimators, 估计量族
( }, o+ i4 m- S, p2 ^! Z$ R# z' _1 aFanning, 扇面
9 g2 W& p7 J8 I, j/ [Fatality rate, 病死率
+ ^8 p' n+ M; ~5 wField investigation, 现场调查, A: G5 M8 j- V, l3 F/ Z
Field survey, 现场调查& |$ @, `! H# w
Finite population, 有限总体' G: K% e% `+ {+ \* t
Finite-sample, 有限样本
% `! B( `& _4 }% }9 Q9 U5 ^+ ]First derivative, 一阶导数
. t" G4 e* A, m- VFirst principal component, 第一主成分
" ^* {% O# G/ y9 Z7 {0 xFirst quartile, 第一四分位数, k- Q9 S2 P9 N' o2 i6 `
Fisher information, 费雪信息量
4 A5 z5 h, J! c" X5 Z" V" D* V" aFitted value, 拟合值* N/ d" K; l0 D, |3 }: ]' ` W
Fitting a curve, 曲线拟合; \5 T* u& O' w7 g- V1 d/ C% y
Fixed base, 定基: Z9 B; R% Z! i2 _+ ^' d
Fluctuation, 随机起伏6 b! k7 {$ _, J
Forecast, 预测9 z: P& h* m6 C# |: z" S& }( A
Four fold table, 四格表" v+ u3 S% a- |
Fourth, 四分点3 r6 z7 Q- o( d* L
Fraction blow, 左侧比率
3 E7 Z4 `, u5 |- c5 ?% I; cFractional error, 相对误差) y& ]! F1 Q( q" @* B
Frequency, 频率( _5 `( F/ T0 U+ R' u) e& P
Frequency polygon, 频数多边图! m) [* w- I. X! R1 z1 ]
Frontier point, 界限点, `& u/ m r! S- w) ]8 [5 x5 p. `$ D1 c
Function relationship, 泛函关系& d5 H: J6 S1 h% r7 ?
Gamma distribution, 伽玛分布
0 v' W C6 H& h+ bGauss increment, 高斯增量- H$ x4 H f3 I! d* T3 ?
Gaussian distribution, 高斯分布/正态分布
4 G% a2 ]+ o, W- Q3 r" tGauss-Newton increment, 高斯-牛顿增量
* o1 Q. `/ o |% A+ O6 bGeneral census, 全面普查
) r% l" ~: [6 d& ?: lGENLOG (Generalized liner models), 广义线性模型
: U8 _ m+ ^5 u2 H. H bGeometric mean, 几何平均数
, k4 \* c" L' v8 r& Q4 H. a5 KGini's mean difference, 基尼均差, [4 C# S- x t& C5 U
GLM (General liner models), 一般线性模型 6 p" w3 J* A" {1 ~& D) e1 H
Goodness of fit, 拟和优度/配合度
+ X- V, S I, T. u2 P4 F. K6 Q+ \Gradient of determinant, 行列式的梯度
2 N. ~* [/ T+ q& X7 ]9 G, f4 ]6 F0 b! FGraeco-Latin square, 希腊拉丁方
4 \1 o6 m7 f6 u% {Grand mean, 总均值
( k$ V/ X0 X8 q" H" { kGross errors, 重大错误
( @# ?4 X( r4 X# o' `Gross-error sensitivity, 大错敏感度
/ p Z; v% ^/ d9 IGroup averages, 分组平均- z$ \- O- M- P4 i8 N4 h% N- k
Grouped data, 分组资料
, Z) e, H* n4 \7 z0 ]+ y& b3 EGuessed mean, 假定平均数
" G; N3 p) u5 _Half-life, 半衰期
: j1 `7 L: c1 n: o, |" mHampel M-estimators, 汉佩尔M估计量
* E& {* r$ Q. J( |# t1 S3 p9 zHappenstance, 偶然事件9 |: x8 w' b0 n+ h1 P I
Harmonic mean, 调和均数
1 k, ?9 U8 h3 \Hazard function, 风险均数
% ~) y7 H" P( B3 G. zHazard rate, 风险率. F6 ]* p/ g; c" P. n( |* J- l8 _
Heading, 标目
+ E# O5 g" h& }9 f& G+ L# x; h! d& qHeavy-tailed distribution, 重尾分布
) `6 h% q M+ c9 N9 V3 b$ r1 wHessian array, 海森立体阵
3 S3 E3 u8 |- E9 H4 i' q5 }Heterogeneity, 不同质
. e5 I6 \. g" }( XHeterogeneity of variance, 方差不齐
! w+ T- e; Q* x8 x1 N! A* ~7 V4 }$ ]Hierarchical classification, 组内分组( U% a* t" |! s/ e" O; ?# e
Hierarchical clustering method, 系统聚类法
l3 I" P! G9 r) }5 T/ C4 k' sHigh-leverage point, 高杠杆率点
& {1 t# i5 S. mHILOGLINEAR, 多维列联表的层次对数线性模型
( p( |" X4 O) e& ]/ p, l/ w. @Hinge, 折叶点
2 y8 I& M6 K9 U, ~' sHistogram, 直方图* Y1 G8 M! `: w& i
Historical cohort study, 历史性队列研究 , G4 M- h" U1 S6 N* h, @
Holes, 空洞$ {6 H9 x. p0 _
HOMALS, 多重响应分析
! v& ?+ E0 s# A2 e: v/ L' V; FHomogeneity of variance, 方差齐性1 r+ O2 L! i' R0 y4 k8 ]/ Z
Homogeneity test, 齐性检验) E( s5 {! d2 Q
Huber M-estimators, 休伯M估计量+ L7 w& l: u/ G
Hyperbola, 双曲线
" B5 t9 m; \( u# |4 W" ZHypothesis testing, 假设检验; _4 a, w+ t7 g+ w, @! t t
Hypothetical universe, 假设总体
- I% q, R; ~1 m! M* _, zImpossible event, 不可能事件$ Q0 K1 Q7 l0 d: I5 N' n
Independence, 独立性
3 m' n9 v4 \5 T* i9 K6 ?' i( T! [Independent variable, 自变量* J0 v5 A6 k3 U
Index, 指标/指数
w/ i1 ^, y! j; xIndirect standardization, 间接标准化法
& V( h; E* g2 WIndividual, 个体+ y$ ^; }6 W0 i) f+ l( @
Inference band, 推断带1 V/ [) X& |9 d9 Y5 h# {4 Z
Infinite population, 无限总体5 {4 ~( I! E7 A
Infinitely great, 无穷大
3 ?6 n4 @' X/ t# yInfinitely small, 无穷小
8 n/ V" O2 o7 K; f) nInfluence curve, 影响曲线
" t4 m6 y9 I; u6 K1 bInformation capacity, 信息容量
1 f, f$ b1 K. p. |1 z5 SInitial condition, 初始条件
' E! P3 X$ h- N7 e! p- [9 d9 {Initial estimate, 初始估计值
( U6 q" s# M( _* n' wInitial level, 最初水平
' }: P4 z; T) J4 u4 T6 i/ J) bInteraction, 交互作用
% o# `# O4 e, [5 R; a6 G5 HInteraction terms, 交互作用项
7 }: R; e0 G. {0 }, x+ {Intercept, 截距1 u. p7 X6 D# t) c0 ?9 g
Interpolation, 内插法
1 n; T% g+ t( R5 k6 L2 x' dInterquartile range, 四分位距
/ B9 P+ D( ]) D' oInterval estimation, 区间估计4 i& w! j9 i5 Y6 N6 n
Intervals of equal probability, 等概率区间+ p. p- L+ N# k' |
Intrinsic curvature, 固有曲率' q& M9 p n: h9 P$ a" [9 \
Invariance, 不变性
. A& ]) j2 p5 {" {9 cInverse matrix, 逆矩阵2 H* U+ b) `6 t* z
Inverse probability, 逆概率
) O$ v( O+ c, M9 n) nInverse sine transformation, 反正弦变换" R* n {* o) \. r
Iteration, 迭代 - J4 b* r! G- ?0 h
Jacobian determinant, 雅可比行列式: F5 P8 Q5 F4 }
Joint distribution function, 分布函数* A- ?$ \+ v. ^1 L% j. \0 e6 K) m
Joint probability, 联合概率
7 S5 y: H& Q2 g& H4 @9 mJoint probability distribution, 联合概率分布: C; \/ f5 B- ]+ T& Y! E& c
K means method, 逐步聚类法
' e7 b% Z8 f& `) E3 z2 `, mKaplan-Meier, 评估事件的时间长度 ) J3 R, G8 c3 L% O
Kaplan-Merier chart, Kaplan-Merier图
1 t5 n) |: Y8 `6 s4 ~Kendall's rank correlation, Kendall等级相关. [+ Y$ g# I7 h& v" Z9 S& H+ a
Kinetic, 动力学
- |8 x$ U4 l5 F+ D4 l/ yKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验 f# m+ @, y; S' u# n6 o
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验; z7 ^" Y) f3 c" B3 ]
Kurtosis, 峰度
3 T# b" v& J' R6 d/ |& S8 e4 ELack of fit, 失拟! O* e2 a& v* m, M! j# W8 v
Ladder of powers, 幂阶梯- n* [7 Q, j0 \1 A% t# S/ ?
Lag, 滞后* d8 o: r/ e1 N
Large sample, 大样本$ }' l$ ?) M- `( n0 P3 i9 E
Large sample test, 大样本检验
) t0 ]# F! Q! `0 J5 GLatin square, 拉丁方1 K5 G0 Y3 I( S, V( n5 I
Latin square design, 拉丁方设计- m/ l1 Y; J8 i [3 {4 L" i
Leakage, 泄漏
4 \! B8 }8 O) uLeast favorable configuration, 最不利构形; M1 x+ p$ Q% ^ p' s. R
Least favorable distribution, 最不利分布
! z4 d% E! ]4 I3 ]) f6 Z7 a7 K& I; kLeast significant difference, 最小显著差法/ P$ F" \0 S7 u8 I
Least square method, 最小二乘法
1 H5 P: o; I3 J/ f4 R% ULeast-absolute-residuals estimates, 最小绝对残差估计; d3 K: K- Y) o6 E1 w: x% ]0 L
Least-absolute-residuals fit, 最小绝对残差拟合
0 I# V$ w# p' H6 n2 s7 w0 kLeast-absolute-residuals line, 最小绝对残差线* Z+ X# h* ^1 _5 o+ s4 D) K0 y
Legend, 图例4 v7 t# M: M# q0 E: }% V# }
L-estimator, L估计量# b: {" X$ @% G' B5 `, E
L-estimator of location, 位置L估计量
3 M) s) i0 w5 J) L& x- OL-estimator of scale, 尺度L估计量% f, T# y% g' r1 R4 d c
Level, 水平- a% H) X1 \ o( Q4 D2 A; t
Life expectance, 预期期望寿命
. A$ f! j7 J @# C8 M6 CLife table, 寿命表
0 ^+ _/ {: H8 b/ N P; ^* XLife table method, 生命表法
2 e/ }- |0 a6 m ]- Y6 Z' `Light-tailed distribution, 轻尾分布2 H9 D1 G8 V* @/ B( s
Likelihood function, 似然函数
& {% S& J! n4 f+ I+ [Likelihood ratio, 似然比2 t# d/ S; R3 [4 m
line graph, 线图, h+ x) g' H' g: t: C* q% I
Linear correlation, 直线相关$ A/ m/ A% M8 A _; P
Linear equation, 线性方程2 c( l2 k. z4 G; \9 ^) ]% o
Linear programming, 线性规划% C5 m: L( w; i/ z2 [
Linear regression, 直线回归
: b) q5 p/ Y2 Z2 _+ N+ L/ Z. vLinear Regression, 线性回归" b! V/ y8 F1 r. O: t6 z5 g& A
Linear trend, 线性趋势! v) ]- ?* w* M4 K* V# h; b. b
Loading, 载荷 8 N9 k5 l, o% \
Location and scale equivariance, 位置尺度同变性) b3 r5 P& t% R; ~) C
Location equivariance, 位置同变性
& `3 q$ m2 |' y& |$ M4 hLocation invariance, 位置不变性) ^+ k, Z+ f! x. B6 u7 n# I: R
Location scale family, 位置尺度族$ c! M1 y. m6 {. `- o
Log rank test, 时序检验 7 A; z( t. x+ C) G1 f/ P) D
Logarithmic curve, 对数曲线9 _" n, q+ h, @. |. {
Logarithmic normal distribution, 对数正态分布
) P% o( \; b" v2 d6 MLogarithmic scale, 对数尺度
" V4 r; P& G; L5 r6 FLogarithmic transformation, 对数变换, O, L2 V; B1 A" t- I+ V0 x7 u
Logic check, 逻辑检查
* u6 q8 F' k" d+ D5 _Logistic distribution, 逻辑斯特分布
/ |& f# n! N" ~7 N3 BLogit transformation, Logit转换! ]8 r) z# ~/ w5 ]3 [( M" `/ D
LOGLINEAR, 多维列联表通用模型 , s0 @$ Z! d) g7 o3 O$ c7 ^
Lognormal distribution, 对数正态分布- Z+ S: ~8 U) ^+ h5 `8 ]
Lost function, 损失函数
+ C/ V7 B0 [4 ]Low correlation, 低度相关 \1 _+ q9 a" ~* I8 X
Lower limit, 下限; _4 A) O( v6 Y. M1 n0 U# @- N
Lowest-attained variance, 最小可达方差# D8 j1 ? R t7 N1 |+ ~7 x" P
LSD, 最小显著差法的简称* Q# S3 ~( r* K' I* r/ g/ u
Lurking variable, 潜在变量
& Z' A$ t9 k j* D4 gMain effect, 主效应9 ]) l+ K9 P, ]1 F0 }- q6 g. K
Major heading, 主辞标目4 A, G' d4 e, x
Marginal density function, 边缘密度函数
) e, R V* \' TMarginal probability, 边缘概率6 h8 T& q( u( a
Marginal probability distribution, 边缘概率分布7 L' t! |+ o* A( O: k% o" [
Matched data, 配对资料
* J$ }) A$ k) _: V1 qMatched distribution, 匹配过分布. u. C, w4 b3 B2 F- F6 j2 R1 J
Matching of distribution, 分布的匹配+ ~+ C# _0 A0 S1 D8 e) ?, P3 L
Matching of transformation, 变换的匹配
/ @* Q/ ]" ?, \- d1 OMathematical expectation, 数学期望
9 P! c+ J d, k6 T4 RMathematical model, 数学模型
4 ?/ A2 X# @8 q; y" J" ^# sMaximum L-estimator, 极大极小L 估计量
7 e' |2 v2 b* Z2 R+ x1 c; QMaximum likelihood method, 最大似然法
* {0 v* K" i, \Mean, 均数
$ h9 h& R0 m6 zMean squares between groups, 组间均方6 \, G8 N+ h1 o: N
Mean squares within group, 组内均方
9 @& k6 Y1 [2 @7 ^Means (Compare means), 均值-均值比较( I6 q* ?2 a( I5 } m' Q
Median, 中位数( F3 O* y9 o; Z" w+ v7 J4 i
Median effective dose, 半数效量
7 p8 c; q! {& u/ Q5 J0 RMedian lethal dose, 半数致死量
) D' p; S0 m. k% D8 `' uMedian polish, 中位数平滑
7 {; f, L( g: V9 |: Z0 \: R; `Median test, 中位数检验) ~, ?& @6 E) @2 l! M" i, o
Minimal sufficient statistic, 最小充分统计量
: d' O: m+ d( J2 u% |! oMinimum distance estimation, 最小距离估计
; O! b0 c: R& I% D EMinimum effective dose, 最小有效量; O& E6 {; V2 `) p, R7 J. [5 t
Minimum lethal dose, 最小致死量: J' v- b+ n1 b/ a+ Y+ U
Minimum variance estimator, 最小方差估计量* {8 L! ^4 _1 Q) \5 W
MINITAB, 统计软件包
: s7 z* ]) S' v, J9 {Minor heading, 宾词标目
" R& I) `! t- ]Missing data, 缺失值0 [/ a/ B/ S9 ~% n9 C' S
Model specification, 模型的确定' g7 c8 ]2 _" H# Z4 z8 r; ^5 ^
Modeling Statistics , 模型统计5 W5 X6 C1 |' `) B8 C% |
Models for outliers, 离群值模型 S! X5 U! U m+ T' I$ _# m) ]# p
Modifying the model, 模型的修正4 N" ^% c W4 _% ?5 S" C
Modulus of continuity, 连续性模
( y% }0 j8 Y; ?+ }3 N% FMorbidity, 发病率 5 W; O, t# A% K, [5 P
Most favorable configuration, 最有利构形% Q! y' u* g$ _
Multidimensional Scaling (ASCAL), 多维尺度/多维标度( A8 F. L6 n8 O* P2 U! g* N9 K
Multinomial Logistic Regression , 多项逻辑斯蒂回归
3 g) ~. G/ O7 P$ wMultiple comparison, 多重比较. y% u% N- Z, V' s' ]
Multiple correlation , 复相关
) ]. o5 {0 d7 J1 @8 Z/ v" O% gMultiple covariance, 多元协方差
( |6 ]4 d* ?2 H( d. vMultiple linear regression, 多元线性回归( F- I' ~! r M1 Z# H- N( i' C& U
Multiple response , 多重选项
$ {. t2 o% s6 w* d4 A: I' LMultiple solutions, 多解
& { Z/ } x) K: L6 W9 J9 ^7 O OMultiplication theorem, 乘法定理0 d( n, }" |$ R5 @0 C
Multiresponse, 多元响应
8 N' _8 h+ j. z/ f6 IMulti-stage sampling, 多阶段抽样
3 {* K5 F; x9 N& K- _Multivariate T distribution, 多元T分布2 d2 Q2 c- E \7 y9 k
Mutual exclusive, 互不相容
- V9 v: \* ?5 P& \7 h+ U$ WMutual independence, 互相独立
: a6 V1 f0 G1 p& @1 ^( p, ^$ v& uNatural boundary, 自然边界
6 v- I. y- _) C, V. hNatural dead, 自然死亡0 a# n2 ~+ d0 U @/ T# X8 e6 c
Natural zero, 自然零
3 ]+ \3 @4 @0 s# Z1 y. H# W+ _Negative correlation, 负相关
0 j" _, b+ R4 ONegative linear correlation, 负线性相关: q1 m+ \3 W/ q# r; C% D
Negatively skewed, 负偏/ O4 {$ N& C! O* u9 W
Newman-Keuls method, q检验( j# b8 h* J* |
NK method, q检验/ t" x+ M* ]0 I8 L9 B/ L
No statistical significance, 无统计意义4 |: m$ n1 [1 H
Nominal variable, 名义变量
# y+ k% ^+ W; T& Z* ^5 t% e9 n6 KNonconstancy of variability, 变异的非定常性
2 C3 u" T; j# O$ LNonlinear regression, 非线性相关
5 _ w; j5 ^% {Nonparametric statistics, 非参数统计
) } ^3 U- w1 S$ @" W4 V ]Nonparametric test, 非参数检验6 n% d: ~8 A8 c$ A3 E, F
Nonparametric tests, 非参数检验 K7 G f3 B+ p8 V! t4 m2 n$ Y E
Normal deviate, 正态离差4 @* ]6 c; P2 _9 T' L: V
Normal distribution, 正态分布
& \( E* N- H" f' E W/ q0 hNormal equation, 正规方程组
# S' T4 G7 C: V2 V# ^- f3 }' sNormal ranges, 正常范围
) \8 B, f: B' G6 UNormal value, 正常值
. |+ C% |- Y1 h+ V1 DNuisance parameter, 多余参数/讨厌参数# L5 c* v7 G1 v5 {
Null hypothesis, 无效假设
3 U; J6 n& F# [' _9 ^: FNumerical variable, 数值变量
: z, w& D3 s# P I7 UObjective function, 目标函数
; D4 I9 ]6 E2 UObservation unit, 观察单位4 Z& O) q+ y- I1 u
Observed value, 观察值
( b8 O7 X2 X( o, n: }4 {9 P8 Z1 OOne sided test, 单侧检验8 R% g; t5 K# y y4 c
One-way analysis of variance, 单因素方差分析/ Y: ?7 X! K# R% O6 _* k( p
Oneway ANOVA , 单因素方差分析
8 q6 T) P; N2 W& v& A# r1 R' T' jOpen sequential trial, 开放型序贯设计: \9 O# H$ _2 K7 C9 K
Optrim, 优切尾
4 ^3 q1 J, A/ {7 _' MOptrim efficiency, 优切尾效率1 f7 n8 q8 q8 L4 }% X( E
Order statistics, 顺序统计量% V n5 M5 m% @* `7 a) M* W
Ordered categories, 有序分类
3 y2 |+ b8 B* J' u( g/ j0 N+ OOrdinal logistic regression , 序数逻辑斯蒂回归0 q7 k0 x$ S7 t. G/ v0 E" U
Ordinal variable, 有序变量" G2 x) ~9 a/ P+ ^
Orthogonal basis, 正交基- t4 M8 Q5 l; H, l6 {
Orthogonal design, 正交试验设计+ m, ^, N- `7 K3 q
Orthogonality conditions, 正交条件
# a- ] h, `% ~, V8 BORTHOPLAN, 正交设计
" L( o8 V0 ]# POutlier cutoffs, 离群值截断点8 `) m' E) ^1 N: W' x# F$ F
Outliers, 极端值
, q/ [- P9 q$ \4 ~' P0 r& R/ TOVERALS , 多组变量的非线性正规相关
/ _: X5 h/ n" j: E. mOvershoot, 迭代过度
) n/ ~ S# F( y8 b kPaired design, 配对设计
8 C/ B8 o; k) z4 b% }; ]Paired sample, 配对样本" t( G) X- k( _/ p
Pairwise slopes, 成对斜率
5 ^( w3 B" `. ?$ pParabola, 抛物线
# z3 Y! j7 ~2 {Parallel tests, 平行试验
' `) b$ Q6 o# k; ~4 ~& B3 M# ]$ `Parameter, 参数
6 A E5 C( D* c# @6 a. q7 e$ s+ FParametric statistics, 参数统计' F% y8 p: I" G% w
Parametric test, 参数检验5 L% E1 G5 o$ K0 _
Partial correlation, 偏相关
- G" s) V; w7 G5 Y/ pPartial regression, 偏回归' u) J1 R! q8 L i6 @
Partial sorting, 偏排序/ I! V4 _# U) q
Partials residuals, 偏残差3 H% O2 n. w( o! [' Y
Pattern, 模式
5 `( i7 N. R* `0 d; OPearson curves, 皮尔逊曲线
) F$ B" b! ~* u( X+ ?3 i9 |Peeling, 退层
& M3 Z, v% [: y3 r/ kPercent bar graph, 百分条形图2 _1 X0 W+ E! n' Q0 D/ m- m
Percentage, 百分比
2 {& z3 v) t5 Z3 |( X$ n. tPercentile, 百分位数6 b" W$ R' H- i: }+ |
Percentile curves, 百分位曲线
8 _7 c; S* }6 ZPeriodicity, 周期性# A# g/ ~: s; w$ i7 s) K- z
Permutation, 排列
2 o6 y5 R3 Z% e; QP-estimator, P估计量
! l! `1 X5 x( ]" F& s2 w) nPie graph, 饼图
( ]# j, x# w0 j* r8 ]. rPitman estimator, 皮特曼估计量* [. n# r5 w. e0 E0 F7 d
Pivot, 枢轴量/ M0 w7 t' w9 ?! d$ j
Planar, 平坦/ H0 i0 Y# _ s0 O" o
Planar assumption, 平面的假设
/ T+ d5 P( { L9 I( q8 [, IPLANCARDS, 生成试验的计划卡. d \; D- @9 `) i+ I3 |" O+ Q; i
Point estimation, 点估计/ X# x* x( X+ |9 \* m
Poisson distribution, 泊松分布
; }( K! d( M" }Polishing, 平滑% T9 P+ k* }; \6 j
Polled standard deviation, 合并标准差
4 ~2 s2 f% \5 N# M# nPolled variance, 合并方差
# Z! |) y `" i4 m$ H4 tPolygon, 多边图0 B8 W- Z" J) M0 I7 j' g8 O
Polynomial, 多项式
8 W, n$ M g: M- S* IPolynomial curve, 多项式曲线- [! P; i8 b* C
Population, 总体
- y: L7 ^; Z5 }Population attributable risk, 人群归因危险度: r( d3 A# ~; H9 z; T; q
Positive correlation, 正相关
7 ^5 E8 _7 A W: S0 {Positively skewed, 正偏
" s4 d9 t; m5 @Posterior distribution, 后验分布" ~6 h7 _8 e3 \5 N5 a% {! \
Power of a test, 检验效能: l4 a2 B1 R" Y n
Precision, 精密度
- T3 k0 y; l) r L% Y+ V2 E DPredicted value, 预测值, r# p- ~7 W C+ `, m! a" T
Preliminary analysis, 预备性分析9 ]4 m% m' B3 {) ~/ r. c, r, j
Principal component analysis, 主成分分析; I6 t2 t N6 a6 R
Prior distribution, 先验分布: y5 i1 D% y- z/ X
Prior probability, 先验概率
& i% k" S* q; M3 z' m& `# Z: D% tProbabilistic model, 概率模型 ?% M: e" b. n c
probability, 概率9 q0 h& s. k+ }" \ g
Probability density, 概率密度+ M) j" L9 d% \
Product moment, 乘积矩/协方差
( l9 {3 I3 S( |% n2 b: w* [Profile trace, 截面迹图
6 f2 v, ?; `( p, TProportion, 比/构成比3 b, X* o% V! o( d/ ?- |3 f. ?
Proportion allocation in stratified random sampling, 按比例分层随机抽样
+ y5 ?2 W- y. C7 _" l4 ?: hProportionate, 成比例
: R7 c0 c5 u* kProportionate sub-class numbers, 成比例次级组含量
! e5 h; g! I; Z. X3 u; { O5 kProspective study, 前瞻性调查) O/ r) V+ { a3 W; D
Proximities, 亲近性 : `0 e; Y! W( B5 d
Pseudo F test, 近似F检验
( \! O, ?6 N0 k1 f# ?Pseudo model, 近似模型
& s* j; w) q7 ^9 E2 A/ GPseudosigma, 伪标准差
- A, U; W# p. R# h0 _Purposive sampling, 有目的抽样
# f- s" X$ S) n3 s g: CQR decomposition, QR分解
% T2 v1 o& x9 c- YQuadratic approximation, 二次近似
! P+ S; {8 e3 g5 F9 _& c1 ?# AQualitative classification, 属性分类1 c, `+ l; X9 w
Qualitative method, 定性方法
: a! O! j) o, i+ UQuantile-quantile plot, 分位数-分位数图/Q-Q图6 n; ?/ L" ]/ S# B! m( o7 c
Quantitative analysis, 定量分析* l$ L% V# s; W6 D/ k/ a J. z
Quartile, 四分位数" }7 X/ v( H! n5 G D5 U
Quick Cluster, 快速聚类7 j3 [% g7 J. e4 k1 v0 p7 s8 ?/ ]. }8 G
Radix sort, 基数排序
- C$ N/ V# j1 m [+ C r. f: ^Random allocation, 随机化分组
* l' c/ {2 ~3 S* ERandom blocks design, 随机区组设计4 v; V/ b# I h: \& Z, w, M) M$ x. U
Random event, 随机事件) ^+ k0 b0 N6 {' M$ Q; i9 ]
Randomization, 随机化5 a. ~9 w/ |7 j6 s- U8 [
Range, 极差/全距4 L# E9 ]3 _1 r1 J& Q5 f8 ]
Rank correlation, 等级相关
1 f/ O' |! }/ A- C1 WRank sum test, 秩和检验( a- s; d) i ?& B& U+ m
Rank test, 秩检验
; Z& v4 k) V& a$ @Ranked data, 等级资料2 @0 Z$ D6 e/ K% j& A
Rate, 比率% o+ H" U' v2 ] k6 S* l
Ratio, 比例
, i# {- U0 w/ URaw data, 原始资料5 n2 \7 {% u& z6 @
Raw residual, 原始残差- W' |4 K# _3 Y
Rayleigh's test, 雷氏检验( }; f% W' S a% K4 B
Rayleigh's Z, 雷氏Z值
]: h% o& u) g- U" n& O5 [Reciprocal, 倒数
7 j2 g& L1 n# O4 ?$ F' W |Reciprocal transformation, 倒数变换
) Q7 `9 g5 z& i9 `Recording, 记录
. U) y2 H4 W: E9 f5 k! k& gRedescending estimators, 回降估计量; Z* ~ ?# k3 R
Reducing dimensions, 降维
% M1 b5 M" G% C4 J9 ]4 i+ f7 NRe-expression, 重新表达
& T& A+ a b' B; t: MReference set, 标准组
* Y* _$ j, B/ E6 A- E" M. ^! lRegion of acceptance, 接受域- |% [) @6 D* \$ a) ]
Regression coefficient, 回归系数
4 s9 w# p6 l" QRegression sum of square, 回归平方和6 G, S* E* V; G* {1 y; X
Rejection point, 拒绝点$ h+ s1 p5 V7 ?! K
Relative dispersion, 相对离散度$ Q& U5 E) `, ?8 m ?! Y- ]! d
Relative number, 相对数/ h+ {- e' k4 h. ^5 D3 T! A5 Z! v
Reliability, 可靠性# f% ?: U" y8 U) q
Reparametrization, 重新设置参数
; @* U4 ?3 H7 {" ~Replication, 重复
8 a$ }2 G* e- y* q j8 a' `6 {$ eReport Summaries, 报告摘要5 O' B/ X1 b$ W/ d" z6 D7 \$ C3 V5 w
Residual sum of square, 剩余平方和9 S* M7 Q1 g! T4 H/ L$ y' s
Resistance, 耐抗性8 ]' v4 m4 }2 K- f9 g
Resistant line, 耐抗线
" J1 a" J# g& G" S! dResistant technique, 耐抗技术/ ]$ T# {, p# K6 Q T
R-estimator of location, 位置R估计量- R% `. ?; C' T8 g t" n
R-estimator of scale, 尺度R估计量* ~1 i" ^, Y4 M! t& h* @) N. u
Retrospective study, 回顾性调查
8 L" B5 y) G: o( J( KRidge trace, 岭迹, i- W: ^' R" p4 M' t, {8 I3 |
Ridit analysis, Ridit分析: P1 s! E4 U# |4 L2 I( j+ U) c
Rotation, 旋转
* D; R) _" N5 Q; O% x' jRounding, 舍入
, k% ] P% r2 URow, 行( d$ R8 B) F( ~% o* }' Y. U. _9 y# \
Row effects, 行效应
+ s) {: y+ w# g9 P$ E5 FRow factor, 行因素4 Z0 n! D4 l, H, R# o' U, _$ v
RXC table, RXC表3 x2 d4 ?8 G/ T
Sample, 样本: u/ {4 t0 c6 {5 k* u; b `
Sample regression coefficient, 样本回归系数
% `( ?) W3 i; D3 Z7 @# z! O; l/ B1 PSample size, 样本量
$ Y6 k8 E. L' z# z9 t6 U$ V5 ? @, ISample standard deviation, 样本标准差7 G9 F* c4 a; n2 y: A
Sampling error, 抽样误差
8 q! h! Y0 n+ T0 }$ y( @SAS(Statistical analysis system ), SAS统计软件包
, s W: Y! ]# W. @+ @" a" W" @* eScale, 尺度/量表4 x5 g, c* Z: l' `0 D
Scatter diagram, 散点图
- _) `' O( P9 E: W2 I2 f6 WSchematic plot, 示意图/简图
7 e2 L9 K) Q6 E8 LScore test, 计分检验
1 w9 Q) u7 V- q P' V2 `Screening, 筛检& M: f3 J, g2 u
SEASON, 季节分析
9 m3 [& r1 l; c6 PSecond derivative, 二阶导数
! J% Q L2 E$ A4 t2 P& {Second principal component, 第二主成分& I- f, c1 T5 D8 E; {
SEM (Structural equation modeling), 结构化方程模型 & y- h# u8 H' A5 b: w9 r
Semi-logarithmic graph, 半对数图
# _& n% H6 Q& {2 A6 PSemi-logarithmic paper, 半对数格纸8 {( O' ^7 o/ S- {
Sensitivity curve, 敏感度曲线. [' \( T9 j; C+ G9 t2 J% _
Sequential analysis, 贯序分析$ ~3 N8 \4 @3 k! r1 c" q! y) ^
Sequential data set, 顺序数据集, G9 i/ w: k( J9 }; i! c" _+ s
Sequential design, 贯序设计$ ^, @9 P3 J9 S, U# l9 b
Sequential method, 贯序法: k! `! r- y, c$ s
Sequential test, 贯序检验法
. B: Z% M2 H' a% e& ~: G) {) r3 MSerial tests, 系列试验3 K( h; h2 y+ h
Short-cut method, 简捷法
. t: l+ |9 Z8 D1 b' g$ kSigmoid curve, S形曲线7 T* P* z8 ~: t2 ~2 y& f& Q
Sign function, 正负号函数* u+ L) p0 p' }7 h
Sign test, 符号检验
9 K- V+ ~$ R; y! Q- y/ ySigned rank, 符号秩
7 {7 r! O" j& S2 m8 r& }Significance test, 显著性检验
K6 R/ s3 S( o7 T& k% U9 B- JSignificant figure, 有效数字
. l7 c" o1 _$ K5 |4 GSimple cluster sampling, 简单整群抽样4 Z4 _1 c+ p6 q! C
Simple correlation, 简单相关* c# G& H6 U; h9 G
Simple random sampling, 简单随机抽样
5 X* M9 p2 Y- K7 rSimple regression, 简单回归& G3 ?) c9 R Y# x" H9 |3 x5 P* Y
simple table, 简单表
4 A/ H6 v# {* Y( |* BSine estimator, 正弦估计量( T$ }* v7 Z* `$ D+ {. _5 F3 L! [
Single-valued estimate, 单值估计
2 V3 _" s- f# m2 j1 h4 i+ i7 KSingular matrix, 奇异矩阵$ u; O" u7 |4 {" m* H8 K5 _9 K
Skewed distribution, 偏斜分布! |+ z3 G! I7 a; p( `
Skewness, 偏度1 E9 C4 A7 k0 Z( A/ h
Slash distribution, 斜线分布+ ?8 S2 B9 i. D$ P0 c
Slope, 斜率0 g) A! o' d2 z4 j3 R _% v# E0 k
Smirnov test, 斯米尔诺夫检验1 x7 n3 A6 K2 R/ H* p; F
Source of variation, 变异来源4 u* K) F: S; d: b& Q
Spearman rank correlation, 斯皮尔曼等级相关
) V- |( `2 P7 s; VSpecific factor, 特殊因子/ o$ [2 x7 b( o6 Z- p& X
Specific factor variance, 特殊因子方差
% D& I; ~6 b2 o9 {- W" O: WSpectra , 频谱
$ o8 \4 V4 o2 s- RSpherical distribution, 球型正态分布
" s1 z6 q7 e) l1 ySpread, 展布3 H) t0 b2 a( s; Y+ q/ p2 q) G9 k
SPSS(Statistical package for the social science), SPSS统计软件包4 X; Z4 |: F7 j6 }3 g) b7 _/ T" q
Spurious correlation, 假性相关$ e, V6 t1 G. b" S
Square root transformation, 平方根变换
' f; Q. j3 q) E$ x; ]Stabilizing variance, 稳定方差
5 p" i8 H/ o, u4 l% Q V+ `8 W+ ]Standard deviation, 标准差
7 U6 {* N, X, hStandard error, 标准误% @$ M; G, {1 t* P& R
Standard error of difference, 差别的标准误& g1 G! l2 q* l% z; @
Standard error of estimate, 标准估计误差2 l$ Y8 Q( _: [2 X
Standard error of rate, 率的标准误
4 f" x2 y7 v) aStandard normal distribution, 标准正态分布
4 G/ r; H- C& \: P0 @4 IStandardization, 标准化1 m' S- E9 o. T$ ~' y9 X& j
Starting value, 起始值
9 K' M5 {7 y+ k' d$ LStatistic, 统计量
1 y8 F1 G( p7 yStatistical control, 统计控制# q% b1 B1 E- h- D8 e0 r
Statistical graph, 统计图9 n- a/ m. {* F9 `/ U6 y: q1 P8 E
Statistical inference, 统计推断
" \2 R# Q9 j; wStatistical table, 统计表
$ d a7 b# o8 U% x2 F8 u0 NSteepest descent, 最速下降法
$ d6 K8 |5 U2 J& dStem and leaf display, 茎叶图
+ u, K- V3 C( ^+ m9 P: w2 g: oStep factor, 步长因子
; A% m+ Z- M6 X1 y+ ~! |6 {Stepwise regression, 逐步回归
. }+ n# H* e% g# K/ y% b$ R: AStorage, 存 e" R! x* B" ?; W# {; a) O
Strata, 层（复数）# }% j, j1 s, ]& E
Stratified sampling, 分层抽样
, K( P2 j- o0 v( v+ D9 |" X& sStratified sampling, 分层抽样
, I1 b" w2 d6 s2 fStrength, 强度
. v" R/ C: ]9 w$ A/ y! N: v, pStringency, 严密性# g* B9 @9 f0 q U; o; f# ]0 c9 Z
Structural relationship, 结构关系
J: b7 X- O% j$ pStudentized residual, 学生化残差/t化残差% F) \; Y2 a( h9 d5 i
Sub-class numbers, 次级组含量
( @/ a# {4 S! T* [/ p# u" uSubdividing, 分割; ]) u6 ~: }7 z7 a( n
Sufficient statistic, 充分统计量
/ J7 s1 |! B5 y- |$ ?& y3 y& {# o& B: P; WSum of products, 积和
5 V3 O. Q7 O$ c: \Sum of squares, 离差平方和7 q9 l# L& e* S2 N0 |2 n2 n& {
Sum of squares about regression, 回归平方和
% D1 H) U" u+ g0 d* Q# V. hSum of squares between groups, 组间平方和1 B: i! ]5 e+ I% z0 l, S3 F
Sum of squares of partial regression, 偏回归平方和: j4 e+ i7 ~' f
Sure event, 必然事件1 A- e6 J( M4 i9 U
Survey, 调查" c! T" F; r( Z3 u( P5 i
Survival, 生存分析
5 o4 }3 [- R! X D- k$ E4 @ n% YSurvival rate, 生存率7 X9 i6 ^4 \$ l1 i! T# T
Suspended root gram, 悬吊根图9 S6 c( ], m( I1 @8 a
Symmetry, 对称7 b7 H1 F% `4 `+ K$ N9 M
Systematic error, 系统误差
$ I) M0 c" ~1 V& Y# i% SSystematic sampling, 系统抽样6 Y8 _9 C( x3 u! f
Tags, 标签8 n& S2 e- v; d- X$ w
Tail area, 尾部面积
. s+ l+ K2 l* @4 C! I4 tTail length, 尾长
) I0 G, P+ _3 H# j! yTail weight, 尾重
4 R0 [) [7 F" \0 ^' \Tangent line, 切线, Y/ N. B. W4 {! n
Target distribution, 目标分布
) F; y* E {8 N/ Q TTaylor series, 泰勒级数4 ~, O0 r+ r! y3 n
Tendency of dispersion, 离散趋势
" ]# J9 w d- c9 ITesting of hypotheses, 假设检验4 l; g$ }% v, [$ ^; v u( [
Theoretical frequency, 理论频数
, ?4 V. w" B+ d+ @4 XTime series, 时间序列
4 k" a: t/ w- [& ]! z0 w2 nTolerance interval, 容忍区间
9 S! n" r+ H2 @" x6 E" M# FTolerance lower limit, 容忍下限
- h0 {0 _( D; A/ }% h/ h8 A9 }8 XTolerance upper limit, 容忍上限
! C4 f$ H% v$ N: `Torsion, 扰率2 v+ ~" @! b( {. ]
Total sum of square, 总平方和4 h: f$ I; A8 X, [" x7 y% h0 V9 L, a
Total variation, 总变异6 ]% x# e$ u( n6 ? X( X
Transformation, 转换
! S9 }# e4 u' @Treatment, 处理
+ Q" T: R) T( D$ l c, @1 T8 R: cTrend, 趋势, K' i& [3 E0 X3 O
Trend of percentage, 百分比趋势9 Z+ D5 t0 d3 E, g4 ]. V
Trial, 试验
$ l& m! ?- }* V! J0 QTrial and error method, 试错法- h0 d: A, |& ~$ G
Tuning constant, 细调常数
4 d: t; e: r$ l7 {Two sided test, 双向检验
$ F3 [1 s$ `" o; kTwo-stage least squares, 二阶最小平方$ u4 w% t8 {: g6 @, C
Two-stage sampling, 二阶段抽样) F$ [% B0 o* i8 s
Two-tailed test, 双侧检验7 O$ p- m' {9 `
Two-way analysis of variance, 双因素方差分析2 g" _8 C9 a& ^2 _" x
Two-way table, 双向表
6 P: N* ?. v# \& K: ]) s, X& `7 M Y& QType I error, 一类错误/α错误% x0 @" B5 z( G1 o E
Type II error, 二类错误/β错误
) e7 k/ E1 A2 o; R4 M; XUMVU, 方差一致最小无偏估计简称- x) r1 P: A% ~9 X0 e
Unbiased estimate, 无偏估计
- V. p5 H" c5 x4 i N/ vUnconstrained nonlinear regression , 无约束非线性回归
2 z! E! C1 m: h" @Unequal subclass number, 不等次级组含量/ v5 h4 o/ ]# F, b9 G6 c Q
Ungrouped data, 不分组资料
4 z5 T+ V& f8 W: c" PUniform coordinate, 均匀坐标
+ _5 w1 h- C+ \% E7 jUniform distribution, 均匀分布/ t% o- J7 U( b) H* Q2 m/ |+ e
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计- e, |/ [) {( o D4 c: _
Unit, 单元4 `- {9 f7 n; `" X+ S7 D! o
Unordered categories, 无序分类
5 |! M: s& } AUpper limit, 上限9 l3 q3 b z" L; A2 G8 q
Upward rank, 升秩* {" @, U8 _) R. i3 w" ~ X
Vague concept, 模糊概念1 q" W( I; v) z$ n% |! _: r2 J" Y6 t
Validity, 有效性
$ n/ ]! D# A, d$ R p2 s/ ?+ PVARCOMP (Variance component estimation), 方差元素估计
; b1 [3 y3 [5 T( @& }Variability, 变异性3 C% G; C/ B& h1 o. L- s6 G" p
Variable, 变量, F7 f9 v/ U" ^
Variance, 方差
' i' L+ k+ f* D4 A! `: {Variation, 变异7 B. W# ~6 O% k3 T& T2 B4 {
Varimax orthogonal rotation, 方差最大正交旋转0 i D( e3 @. c" J: K
Volume of distribution, 容积6 L2 p& m- q E- S& o
W test, W检验
* W& P$ Z, B/ y2 q9 pWeibull distribution, 威布尔分布
$ l: B- }/ s' H) V" r9 qWeight, 权数
. b- z# n) Q+ A& ?+ A+ ?Weighted Chi-square test, 加权卡方检验/Cochran检验
* y' L3 N, a- y, t7 uWeighted linear regression method, 加权直线回归9 C$ n$ M: G& `: x# W
Weighted mean, 加权平均数
6 |, t2 [0 W& w3 O$ Q& nWeighted mean square, 加权平均方差' W( h |. w0 {4 E, `
Weighted sum of square, 加权平方和! z% w6 y' q- ^) u/ `/ D r
Weighting coefficient, 权重系数6 H; Y. n4 H& V9 U# ]& Q8 ?
Weighting method, 加权法
0 | P% {! W) D; P, ^. gW-estimation, W估计量$ E: Z+ }& h2 B5 y5 t6 e L" w
W-estimation of location, 位置W估计量
2 D6 E3 q8 y# C# C" s2 ^5 gWidth, 宽度
) n* n0 @5 {3 ]; h2 HWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
8 }9 R- K2 u0 I) O; ?4 tWild point, 野点/狂点+ B: {4 Y# k( k: I4 M4 v6 J: f8 A
Wild value, 野值/狂值
2 u/ S7 P' S4 E, S- L- i' OWinsorized mean, 缩尾均值
- ]( y/ q1 @: ^4 ]Withdraw, 失访 ! ~: s- h& \) y
Youden's index, 尤登指数
, `+ G! }7 l B) N0 }" n; rZ test, Z检验
$ X! X3 ^1 J: W5 U" \1 ?Zero correlation, 零相关# z& v+ \7 p8 @3 R1 x8 L
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
